Bidding Optimisation in Ad Auctions

Ad auction bidding strategy for several competing performance metrics as a constrained optimisation problem

Here at travel audience we are in the business of adtech, i.e. programmatic online advertising. As a Demand Side Platform (DSP), our algorithms find the optimal audience to target in order to bring value to our clients - the advertisers. Targeting the identified audience with ads proceeds via participating in an online auction, which is triggered every time a user visits a website run by a publisher who wants to monetize the visits. All DSPs participating in the auction submit their bids and the highest bid wins the right to show an ad from a client to the website visitor.

Now, this of course is an extreme simplification of the process every DSP executes in less than a 100 milliseconds for each of the tens of thousands bid requests they receive every second. Does the bid request for given user fit the targeting criteria of the clients? Which ad from which campaign of which advertiser should one pick for this bid request? Which provides most value to the client and how to predict this value? What is the right bid given the expected value to the advertiser and our expected margin?

The fascinating, but also daunting aspect of adtech is that all such questions need to be answered. Answering them all at the same time is an impossible task though, so it is better to break them into subproblems of the full bidding logic. Roughly speaking, the key components of the bidding logic are:

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